Professional Certification Program
Professional education for the people who manage, advise, and optimize employer-sponsored health plans.
Certified Professional in Model Optimal Care — the credential that proves your mastery of data-driven, fiduciary-grade health plan management.
Certified Professional in
Model Optimal Care
The CP-MOC designation is a professional certification for individuals who demonstrate mastery of the Model Optimal Care framework. It is designed for benefits directors, HR executives, consultants, brokers, TPAs, and other professionals who manage or advise employer-sponsored health plans.
This certification covers the full scope of the MOC framework: Transparency, Accountability, Integration, Engagement, and Technology Enablement. Candidates complete a structured, self-paced online course, pass a comprehensive assessment, and earn a credential that signals their commitment to data-driven, fiduciary-grade health plan management.
The CP-MOC program qualifies for tuition reimbursement under IRS Section 127, which lets companies pay up to $5,250 per employee per year for continuing education, tax-free. That more than covers the full cost of your CP-MOC certification. Ask your HR or benefits team about your educational assistance program. We will send them the course outline, syllabus, and invoice directly to simplify your request. Most approvals close within two weeks.
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A comprehensive sequence of professional courses covering the full scope of healthcare waste reduction, clinical management, and AI-driven strategy.
The Model Optimal Care Academy offers a growing library of professional courses for healthcare benefits professionals. Each course is designed to deliver practical skills you can apply immediately after taking each course.
A foundational course for organizations considering the transition from fully insured to self-funded health plans. Covers the economic drivers behind self-funding, the regulatory framework under ERISA, stop-loss coverage structures, vendor selection (TPA, ASO, PBM), plan design fundamentals, and a 15-week implementation timeline. Ideal for HR leaders, finance professionals, and benefits consultants advising mid-market employers.
Learn how to assess, quantify, and manage risk within self-insured health plans. Covers actuarial concepts in accessible terms, including specific and aggregate stop-loss thresholds, risk modeling, risk stratification, large claims probability modeling, and demographic risk adjustment. Build skills in evaluating plan exposure, setting clinical groupers and AI models, and communicating risk scenarios to executive stakeholders.
A practical introduction to healthcare data analytics for benefits professionals. Covers core concepts in claims data structure, key performance indicators for health plan evaluation, population health metrics, trend analysis, and benchmarking. Includes hands-on exercises in interpreting medical and pharmacy utilization reports. Designed for professionals who work with data daily but want a stronger analytical foundation.
Learn how to design, build, and present executive-level health plan reports that drive decision-making. Covers report design principles, data visualization best practices, narrative construction for different audiences (C-suite, benefits teams, employee communications), and dashboard layout. Includes templates and frameworks for large claims summaries, pharmacy savings analyses, ER utilization trends, and risk utilization dashboards.
An introduction to data warehousing tailored for the self-insured health plan ecosystem. Covers data architecture fundamentals, ETL processes for medical and pharmacy claims, data integration across multiple sources (eligibility, labs, wellness, premiums), data quality and validation, and the role of a centralized data repository in supporting analytics, reporting, and AI-driven insights. Designed for technical professionals and benefits leaders.
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Get the latest on healthcare cost containment, the MOC framework, and upcoming Academy courses.
Get the latest on healthcare cost containment, the MOC framework, and upcoming Academy courses.
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